• Title/Summary/Keyword: 컴퓨터 코드 최적화

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Performance of Multiuser Detector Based on Radial Basis Function for DS-CDMA Power Line Communication Systems (DS-CDMA 기반 전력선 통신 시스템을 위한 방사형 기저 함수를 이용하는 다중 사용자 검출기의 성능)

  • Hwang, Yu Min;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.12 no.1
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    • pp.1-5
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    • 2017
  • In this paper, multiuser detector (MUD) based on radial basis function (RBF) is proposed and simulated for a multicode direct sequence/code division multiple access (DS/CDMA) system in a multipath fading channel. The performance of RBF-based MUD is compared with that of many suboptimal multiuser detectors in terms of bit error probability. From the simulation results, it is confirmed that the RBF-based MUD outperforms decorrelating detector, and achieves near-optimum performance under various environments. The results in this paper can be applied to design of MUD for a multicode DS/CDMA system.

Extracting Scheme of Compiler Information using Convolutional Neural Networks in Stripped Binaries (스트립 바이너리에서 합성곱 신경망을 이용한 컴파일러 정보 추출 기법)

  • Lee, Jungsoo;Choi, Hyunwoong;Heo, Junyeong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.4
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    • pp.25-29
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    • 2021
  • The strip binary is a binary from which debug symbol information has been deleted, and therefore it is difficult to analyze the binary through techniques such as reverse engineering. Traditional binary analysis tools rely on debug symbolic information to analyze binaries, making it difficult to detect or analyze malicious code with features of these strip binaries. In order to solve this problem, the need for a technology capable of effectively extracting the information of the strip binary has emerged. In this paper, focusing on the fact that the byte code of the binary file is generated very differently depending on compiler version, optimazer level, etc. For effective compiler version extraction, the entire byte code is read and imaged as the target of the stripped binaries and this is applied to the convolution neural network. Finally, we achieve an accuracy of 93.5%, and we provide an opportunity to analyze stripped binary more effectively than before.

Development of Unmanned Payment System based on QR Code optimized for Non-face-to-face (비대면에 최적화된 QR 코드기반 무인 결제 시스템 개발)

  • Kim, Yeon-Woo;Hwang, Seung-Yeon;Shin, Dong-Jin;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.4
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    • pp.165-170
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    • 2022
  • By reducing time spent outside, a shopping system was developed for middle-aged and elderly people who mainly use neighborhood marts and neighborhood mart managers. The main functions of this app are direct shopping and online shopping, and it was developed using QR code using Zxing library on Android and Kakao Map using Kakao API. In addition, it provides information such as payment statistics and bulletin board posts that members need through recycler view and graphs in an easy-to-read manner. Through this system, members can efficiently manage by reducing fatigue when using the mart through direct purchase using QR code and delivery through map, and reducing manpower wastage as a mart manager. Also, as a mart manager, more consumers will be able to sell more items.

A Study on Scalability of Profiling Method Based on Hardware Performance Counter for Optimal Execution of Supercomputer (슈퍼컴퓨터 최적 실행 지원을 위한 하드웨어 성능 카운터 기반 프로파일링 기법의 확장성 연구)

  • Choi, Jieun;Park, Guenchul;Rho, Seungwoo;Park, Chan-Yeol
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.10
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    • pp.221-230
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    • 2020
  • Supercomputer that shares limited resources to multiple users needs a way to optimize the execution of application. For this, it is useful for system administrators to get prior information and hint about the applications to be executed. In most high-performance computing system operations, system administrators strive to increase system productivity by receiving information about execution duration and resource requirements from users when executing tasks. They are also using profiling techniques that generates the necessary information using statistics such as system usage to increase system utilization. In a previous study, we have proposed a scheduling optimization technique by developing a hardware performance counter-based profiling technique that enables characterization of applications without further understanding of the source code. In this paper, we constructed a profiling testbed cluster to support optimal execution of the supercomputer and experimented with the scalability of the profiling method to analyze application characteristics in the built cluster environment. Also, we experimented that the profiling method can be utilized in actual scheduling optimization with scalability even if the application class is reduced or the number of nodes for profiling is minimized. Even though the number of nodes used for profiling was reduced to 1/4, the execution time of the application increased by 1.08% compared to profiling using all nodes, and the scheduling optimization performance improved by up to 37% compared to sequential execution. In addition, profiling by reducing the size of the problem resulted in a quarter of the cost of collecting profiling data and a performance improvement of up to 35%.

Lip-Synch System Optimization Using Class Dependent SCHMM (클래스 종속 반연속 HMM을 이용한 립싱크 시스템 최적화)

  • Lee, Sung-Hee;Park, Jun-Ho;Ko, Han-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.7
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    • pp.312-318
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    • 2006
  • The conventional lip-synch system has a two-step process, speech segmentation and recognition. However, the difficulty of speech segmentation procedure and the inaccuracy of training data set due to the segmentation lead to a significant Performance degradation in the system. To cope with that, the connected vowel recognition method using Head-Body-Tail (HBT) model is proposed. The HBT model which is appropriate for handling relatively small sized vocabulary tasks reflects co-articulation effect efficiently. Moreover the 7 vowels are merged into 3 classes having similar lip shape while the system is optimized by employing a class dependent SCHMM structure. Additionally in both end sides of each word which has large variations, 8 components Gaussian mixture model is directly used to improve the ability of representation. Though the proposed method reveals similar performance with respect to the CHMM based on the HBT structure. the number of parameters is reduced by 33.92%. This reduction makes it a computationally efficient method enabling real time operation.

Compact Implementation and Analysis of Rainbow on 8bits-Microcontroller Uunit (8비트 마이크로컨트롤러 유닛 상에서 Rainbow 최적화 구현 및 분석)

  • Hong, Eungi;Cho, Seong-Min;Kim, Aeyoung;Seo, Seung-Hyun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.4
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    • pp.697-708
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    • 2019
  • In this paper, we propose and implement a method to optimize Rainbow for 8 bit MCU(Microcontroller Unit). As quantum computers have been developed, the security of existing cryptography, especially the signature algorithms, has been threatened, so it is necessary to apply a signature scheme with a quantum-resistance to IoT devices. Currently, the proposed PQC(Post Quantum Cryptography) are lattice-based, hash-based, code-based, and MQ(Multivariate Quadratic)-based cryptographic algorithms and signature schemes. In particular, MQ-based signature schemes are faster than conventional signature schemes and are suitable for IoT devices Do. However, it is difficult to apply 8-bit MCU, which has a large key length and large number of computations, to the memory and performance of IoT devices. In this paper, we propose a method of storing Rainbow, which is a MQ-based signing scheme, in 8-bit MCU by dividing the key and optimizing the computation method. By reducing the memory consumption and improving the algorithm speedily, Compare performance.

Developing Programming Education Software with Generative AI (생성형 인공지능을 활용한 프로그래밍 교육 소프트웨어 개발)

  • Do-hyeon Choi
    • Journal of Practical Engineering Education
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    • v.15 no.3
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    • pp.589-595
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    • 2023
  • Artificial intelligence(AI) is spurring advancements in EdTech, the merger of technology and education. This includes the creation of effective learning materials and personalized student experiences. Our study focuses on developing a programming education software that employs state-of-the-art generative AI. Our software also includes prompts optimized for programming code analysis, which are based on the well-known ChatGPT API. Furthermore, the necessary functions for acquiring programming skills were created with a user interface and developed as a question-and-answer template function based on an AI chatbot. The objective of this study is to guide the development of educational programmes that make use of generative AI.

Memory Hierarchy Optimization in Embedded Systems using On-Chip SRAM (On-Chip SRAM을 이용한 임베디드 시스템 메모리 계층 최적화)

  • Kim, Jung-Won;Kim, Seung-Kyun;Lee, Jae-Jin;Jung, Chang-Hee;Woo, Duk-Kyun
    • Journal of KIISE:Computer Systems and Theory
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    • v.36 no.2
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    • pp.102-110
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    • 2009
  • The memory wall is the growing disparity of speed between CPU and memory outside the CPU chip. An economical solution is a memory hierarchy organized into several levels, such as processor registers, cache, main memory, disk storage. We introduce a novel memory hierarchy optimization technique in Linux based embedded systems using on-chip SRAM for the first time. The optimization technique allocates On-Chip SRAM to the code/data that selected by programmers by using virtual memory systems. Experiments performed with nine applications indicate that the runtime improvements can be achieved by up to 35%, with an average of 14%, and the energy consumption can be reduced by up to 40%, with an average of 15%.

Cervical Cell Classification using Genetic Programming and Central tendency of Image (영상의 대표값과 유전자 프로그래밍을 이용한 자궁경부세포진 영상 인식)

  • 김재륜;김백섭;이헌길;하진영
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.283-285
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    • 2001
  • 유전자 프로그래밍은 프로그램 자동생성 도구이다. 문제를 해결하는 프로그램코드를 프로그래머가 직접 구현하는 것이 아니라, 적절한 초기값만을 입력하여 컴퓨터가 스스로 적합한 해를 찾아내도록 하는 방법이다. 유전자 프로그래밍은 생물의 진화개념에서 얻어진 여러 아이디어를 사용하여 최적화된 해를 찾아낸다. 본 논문에서는 세포영상인식 문제를 해결하기 위하여 유전자 프로그래밍을 사용하였다. 실험에 사용된 영상은 자궁경부세포진 영상이다. 여러 가지 종류와 상태의 세포들이 뒤섞여 있어 분석하기에 힘들다는 것이 이 영상의 특징이다. 주어진 문제는 샘플 영상이 암인가 아닌가를 판별하는 것이다. 유전자 프로그래밍을 적용하기 위하여 사용한 특징값들은 영상에서 찾을 수 있는 가장 단순한 대표값들과, 산술 및 논리연산자들이다. 실험결과 실제 인식기 제작에 바로 적용하기엔 무리가 있지만, 80%정도를 제대로 판별해 낼수 있었다. 인식률이 낮은 이유는 사용한 특징들이 영상의 정보를 잘 흡수하지 못했기 때문이라 여겨지고, 앞으로 지나치게 복잡하지 않으면서 여상의 특징을 잘 표현하는 특징값들을 찾는 것이 향후과제이다.

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Real-time BCC Volume Isosurface Ray Casting on the GPU (GPU를 이용한 실시간 BCC 볼륨 등가면 레이 캐스팅)

  • Kim, Minho;Lee, Young-Joon
    • Journal of the Korea Computer Graphics Society
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    • v.18 no.4
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    • pp.25-34
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    • 2012
  • This paper presents a real-time GPU (graphics processing unit) ray casting scheme for rendering isosurfaces of BCC (body-centered cubic) volume datasets. A quartic spline field is built using the 7-direction box-spline filter accompanied with a quasi-interpolation prefilter. To obtain an interactive rendering speed on the graphics hardware, the shader code was optimized to avoid lookup table and conditional branches and to minimize data fetch overhead. Compared to previous implementations, our work outperforms the comparable one by more than 20% and the rendering quality is superior than others.